DC Motor Fault Analysis with the Use of Acoustic Signals, Coiflet Wavelet Transform, and K-Nearest Neighbor Classifier

This paper focuses on testing the monitoring system of the Direct Current motor. This system gives the possibility of diagnosing various types of failures by means of analysis of acoustic signals. The applied method is based on a study of acoustic signals generated by the DC motor. A study plan of the DC motor’s acoustic signal was proposed. Studies were conducted for a faultless DC motor and Direct Current motor with 3 shorted rotor coils. Coiflet wavelet transform and K-Nnearest neighbor classifier with Euclidean distance were used to identify the incipient fault. This approach keeps the motor operating in acceptable condition for a long time and is also inexpensive

Multiplicity dependence of the average transverse momentum in pp, p-Pb, and Pb-Pb collisions at the LHC

The average transverse momentum (p(T)) versus the charged-particle multiplicity N-ch was measured in p-Pb collisions at a collision energy per nucleon-nucleon root S-NN = 5.02 TeV and in pp collisions at collision energies of root s = 0.9, 2.76, and 7 TeV in the kinematic range 0.15 < p(T) < 10.0 GeV/c and vertical bar eta vertical bar < 0.3 with the ALICE apparatus at the LHC. These data are compared to results in Pb-Pb collisions at root S-NN = 2.76 TeV at similar charged-particle multiplicities. In pp and p-Pb collisions, a strong increase of (p(T)) with N-ch is observed, which is much stronger than that measured in Pb-Pb collisions. For pp collisions, this could be attributed, within a model of hadronizing strings, to multiple-parton interactions and to a final-state color reconnection mechanism. The data in p-Pb and Pb-Pb collisions cannot be described by an incoherent superposition of nucleon-nucleon collisions and pose a challenge to most of the event generators. (C) 2013 CERN. Published by Elsevier B.V. All rights reserved